DBMS > Fujitsu Enterprise Postgres vs. MongoDB vs. Titan

System Properties Comparison Fujitsu Enterprise Postgres vs. MongoDB vs. Titan

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS

Document store

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.26
Rank	#295	Overall
	#132	Relational DBMS

Score	402.51
Rank	#5	Overall
	#1	Document stores

Website

www.postgres.global.fujitsu.com

www.mongodb.com

github.com/thinkaurelius/titan

Technical documentation

www.postgres.global.fujitsu.com/product-manuals

www.mongodb.com/docs/manual

github.com/thinkaurelius/titan/wiki

Developer

Fujitsu Limited

MongoDB, Inc

Aurelius, owned by DataStax

Initial release

2009

2012

Current release

Fujitsu Enterprise Postgres 16, May 2024

7.0.5, January 2024

License

Commercial or Open Source

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Server operating systems

Linux
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

yes

Secondary indexes

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

JavaScript

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

Relationships in graph

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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